‘Student Needs’! Columns I through O contain information on when each student attends an intervention class. Intervention classes take place during the second half of the classes (Science or social studies) or during the second half of Co-taught classes (math or ELA). Science and social studies interventions are done on either Monday/Wednesday or Tuesday/Friday (Thursdays have a special schedule that we do not need to consider). Math and ELA interventions occur on all four days.
In ‘Student Master’!, each student’s schedule is listed for both MW and TF. In Columns E, G, K, and M, I would like to populate any of the interventions that are listed in the ‘Student Needs’! sheet. For instance, Lindsey Lukowski has Social Skills on MW2 (Mondays and Wednesdays 2nd hour). So in cell ‘Student Master’! G31 should return “Social Skills”.
William Watters is getting Read Naturally and Reading Comp during his 5th Hour Co-Taught ELA. So ‘Student Master’! K51 and K52 should both return Read Naturally & Reading Comp (in the same cell).
Here is the workbook:
https://docs.google.com/spreadsheets/d/1aW7ExATzMn9Rf8IFLI4v-CQiqsXnxyDm8PxqMW999bY/edit?usp=sharing
Here is a complex functions that seems to do what you want. I have tested it in a copy of your sheet
Just Change E$2 for different columns.
=IFERROR(INDIRECT("'Student Needs'!"&CHAR(72+IFERROR(MATCH("HR "&E$2,ARRAYFORMULA(REGEXEXTRACT(INDIRECT("'Student Needs'!I"®EXEXTRACT($A3,"[0-9]+")+5&":N"®EXEXTRACT($A3,"[0-9]+")+5),"[A-Z ]+[0-9]")),0),MATCH($C3,ARRAYFORMULA(REGEXEXTRACT(INDIRECT("'Student Needs'!I"®EXEXTRACT($A3,"[0-9]+")+5&":N"®EXEXTRACT($A3,"[0-9]+")+5),"[A-Z]+")),0)))&5))
Also I am not sure where "6- Science" should go? Is this also HR 6?
In order for it to work with actual
=IFERROR(INDIRECT("'Student Needs'!"&CHAR(72+IFERROR(MATCH("HR "&E$2,ARRAYFORMULA(REGEXEXTRACT(INDIRECT("'Student Needs'!I"&ROW(VLOOKUP($A3,'Student Needs'!$A$1:$B,2,false))&":N"&ROW(VLOOKUP($A3,'Student Needs'!$A$1:$B,2,false))),"[A-Z ]+[0-9]")),0),MATCH($C3,ARRAYFORMULA(REGEXEXTRACT(INDIRECT("'Student Needs'!I"&ROW(VLOOKUP($A3,'Student Needs'!$A$1:$B,2,false))&":N"&ROW(VLOOKUP($A3,'Student Needs'!$A$1:$B,2,false))),"[A-Z]+")),0)))&5))
Related
I've got a SpatRaster of (150 x 150 x 1377) that shows temporal evolution of precipitations. Each layer is a given hour in a 2-month interval, but some hours are missing, and the dataset isn't continuous. The layers names are strings as "YYYYMMDDhhmm".
I need to find the mean value every three hours even on whole intervals or on missing-data intervals. On entire ones I want to average three data and on missing-data ones I would like to average two of them or, if two are missing, to select the unique value as the averaged one.
How can I use data names to select how to act?
I've already tried this code but I'm averaging on three continuous layers by index and not by hours. How can I convert names in DateTime form from "tidyverse" in order to use rollapply() to see if two steps back I find the DateTime I am expecting? Is there any other method to check this out?
HSAF=rast(c((paste0(resfolder, "HSAF_final1_5.tif")),(paste0(resfolder, "HSAF_final6_10.tif")),(paste0(resfolder, "HSAF_final11_15.tif")),
(paste0(resfolder, "HSAF_final16_20.tif")),(paste0(resfolder, "HSAF_final21_25.tif")),(paste0(resfolder, "HSAF_final26_30.tif")),
(paste0(resfolder, "HSAF_final31_N04.tif")),(paste0(resfolder, "HSAF_finalN05_N08.tif")),(paste0(resfolder, "HSAF_finalN09_N13.tif")),
(paste0(resfolder, "HSAF_finalN14_N18.tif")),(paste0(resfolder, "HSAF_finalN19_N23.tif")),(paste0(resfolder, "HSAF_finalN24_N28.tif")),
(paste0(resfolder, "HSAF_finalN29_N30.tif"))))
index=names(HSAF)
j=2
for (i in seq(1,3, by=3))
{third_el<- HSAF[index[i+j]]
second_el <- HSAF[index[i+j-1]]
first_el<- HSAF[index[i+j-2]]
newraster<- c(first_el, second_el, third_el)
newraster<- mean(newraster, filename=paste0(tempfile(), ".tif"))
names(newraster)<- paste0(index[i+j-2],index[i+j-1],index[i+j])
}
for (i in seq(4,1374 , by=3))
{ third_el<- HSAF[index[i+j]]
second_el <- HSAF[index[i+j-1]]
first_el<- HSAF[index[i+j-2]]
subraster<- c(first_el, second_el, third_el)
subraster<- mean(subraster, filename=paste0(tempfile(), ".tif"))
names(subraster)<- paste0(index[i+j-2],index[i+j-1],index[i+j])
add(newraster)<- subraster
}
So I have two csv files, one is the all member information, one is a poll event result,
which is like:
Member information:
[Member Name],[Member Tier]
Apple, Bronze
Banana, Silver
Cat, Gold
Poll event result:
[Member Name],[OptionA],[OptionB],[OptionC]
Apple,0,0,1
Banana,1,0,0
Cat,0,1,0
I want to do is weight the vote value with member's tier, for example, Cat is gold member so in this poll OptionB will win.
But the poll csv file is lack of member's tier parameter, so, I'm thinking to do a function like:
Create list "tier Bronze","tier Silver","tier Gold"
in member information file, loop for everyone, if tier match, add to that list
and then go to poll file, loop for everyone, if name match the name in tier list, mark them.
I'm not sure is this the right way, and how to do it, any help will be appreciated :^)
What you need is a vlookup function.
Take 2 lists with member name (as ID) in first left column and tier in 2nd and then use vlookup.
Put vlookup on the right part of your poll table and write:
=vlookup(ID location;range with poll results;2;false)
Then copy down vlookup formula
Or you can do it in more elegant way using Arrayformula:
=ArrayFormula(
ifna(
vlookup(E3:E;$B$3:$C;2;false)
)
)
The reference manual has this to say about the table.move function, introduced in Lua 5.3:
table.move (a1, f, e, t [,a2])
Moves elements from table a1 to table a2, performing the equivalent to the following multiple assignment: a2[t],··· = a1[f],···,a1[e]. The default for a2 is a1. The destination range can overlap with the source range. The number of elements to be moved must fit in a Lua integer.
This description leaves a lot to be desired. I'm hoping for a general, canonical explanation of the function that goes into more detail than the reference manual. (Oddly, I could not find such an explanation anywhere on the web, perhaps because the function is fairly new.)
Particular points I am still confused on after reading the reference manual's explanation a few times:
When it says "move", that means the items are being removed from their original location, correct? Do the indices of items above the removed items shift down to fill the gaps? If so, and we're moving within the same table, does t point to the original location before anything starts moving?
Is there some significance to the choice of index letters f, e, and t?
There is no similar function in any other language I know. What's an example of how I might use this? Since it's one of only seven table functions, I presume it's quite useful.
Moves elements from table a1 to table a2, performing the equivalent to the following multiple assignment a2[t],··· = a1[f],···,a1[e]
Maybe they could have added the information this is done using consecutive integer values from f to e.
If you know Lua a bit more you'll know that a Lua table has no order. So the only way to make that code work is to use consecutive integer keys. Especially as the documentation mentions a source range.
Giving the equivalent syntax is the most unambiguous way of describing a function.
If you know the very basic concept of multiple assignment in Lua (see 3.3.3. Assignment) , you know what this function does.
table.move(a1, 1, 4, 6, a2) would copy a1[1], a1[2], a1[3], a1[4] into a2[6], a2[7], a2[8], a2[9]
The most common usecase is probably to get a subset of a list.
local values = {1,45,1,44,123,2354,321,745,1231}
old syntax:
local subset = {}
for i = 3, 7 do
table.insert(subset, values[i])
end
new:
local subset = table.move(values, 5, 7, 1, {})
Or maybe you quickly want to remove the last 3 values from a table?
local a = {1,2,3,4,5,6,7}
table.move({}, 1,3,#a-2, a)
I got a few - company, location and product details to store in a db.
sample data
company location product
------------------------------
abc hilltop alpha
abc hilltop beta
abc riverside alpha
abc riverside beta
buggy underbridge gama
buggy underbridge theta
buggy underbridge omega
The relationships are multi-valued, as I understand. And the data needs to be normalized as the MVD's are
not derived from a candidate key (company ->> location and company ->> product where company is not a candidate key)
or the union does not make the whole set (company U location < R and so with product).
But my colleague disagrees with me, who insists that for a relation to have multi-valued dependency at least four same values in company column should exist for each company. i.e
t1(company) = t2(company) = t3(company) = t4(company),
for company abc this is true. But for company "buggy", which does only one product in three locations, this is untrue.
For the formal definition and similar examples I refernced:
https://en.wikipedia.org/wiki/Multivalued_dependency
and Fourth_normal_form example also on wiki.
I know my colleague is being pedagogy, but I too started seeing the same question after reading the formal definition. (After all these are derived on mathematical basis.)
update: I am not asking how to normalize this data in to 4NF, I think I know that. (I need to break it in to two tables 1) company - location and 2) company - product.
which I have done already.
Can some one explain how this relation is still a MVD even though it does not satisfy the formal definition?
Detailed explanations are very much welcome.
"There exist" says some values exist, and they don't have to be different. EXISTS followed by some name(s) says that there exist(s) some value(s) referred to by the name(s), for which a condition holds. Multiple names can refer to the same value. (FOR ALL can be expressed in terms of EXISTS.)
The notion of MVD can be applied to both variables and values. In fact the form of the linked definition is that a MVD holds in the variable sense when it holds in the value sense "in any legal relation". To know that a particular value is legal, you need business knowledge. You can then show whether that value satisfies an MVD. But to show whether its variable satisfies the MVD you have to show that the MVD is satisfied "in any legal relation" value that the variable can hold. One valid value can tell you that a MVD doesn't hold in (it and) its variable, but it can't tell you that a MVD does hold in its variable. That requires more business knowledge.
You can show that this value violates 4NF by using that definition of MVD. The definition says that a relation variable satisfies a MVD when a certain condition holds "for any valid relation" value:
for all pairs of tuples t1 & t2 in r such that t1[a] = t2[a] there exist tuples t3 & t4 [...]
For what MVD and values for t1 & t2 does your colleague claim there doesn't exist values for t3 & t4? There is no such combination of MVD and values for t1 & t2. Eg for {company} ↠ {product} and t1 & t2 both (buggy, underbridge, gamma), we can take (company, underbridge, gamma) as a value for both t3 & t4, and so on for all other choices for t1 & t2.
Another definition for F ↠ T holding is that binary JD (join dependency) *{F U T, F U (A - T)} holds, ie that the relation is equal to the join of its projections on F U T & F U (A - T). This definition might be more immediately helpful to you & your colleague in that it avoids the terminology that you & they are misinterpreting. Eg your example data is the join of these two of its projections:
company location
--------------------
abc hilltop
abc riverside
buggy underbridge
company product
----------------
abc alpha
abc beta
buggy gamma
buggy theta
buggy omega
So it satisfies the JD *{{company, location}, {company, product}}, so it satisfies the MVDs {company} ↠ {location} and {company} ↠ {product} (among others). (Maybe you will be able to think of examples of relations with zero, one, two, three etc tuples for which one or more (trivial and/or non-trivial) MVDs hold.)
Of course, the two definitions are two different ways of describing the same condition.
PS 1 Whenever a FD F → T holds, the MVD F ↠ T holds. For a relation in BCNF, the MVDs that violate 4NF & 5NF are those not so associated with FDs.
PS 2 A relation variable is meant to hold a tuple if and only if it makes a true statement in business terms when its values are substituted into a given statement template, or predicate. That plus the JD definition for MVD gives conditions for a relation variable satisfying a MVD in business terms. Here our predicate is of the form ...company...location...product.... (Eg company namedcompanyis located atlocationand makes productproduct.) It happens that this MVD holds for a variable when for all valid business situations, FOR ALL company, location, product,
EXISTS product [...company...location...product...]
AND EXISTS location [...company...location...product...]
IMPLIES ...company...location...product...
I have a ClientDataSet with the following data
IDX EVENT BRANCH_ID BRANCH
1 E1 7 B7
2 E2 5 B5
3 E3 7 B7
4 E4 1 B1
5 E5 2 B2
6 E6 7 B7
7 E7 1 B1
I need to transform this data into
IDX EVENT BRANCH_ID BRANCH
1 E1 7 B7
2 E2 5 B5
4 E4 1 B1
5 E5 2 B2
The only fields of importance are the BRANCH_ID and BRANCH
and BRANCH_ID must be unique
As there is a lot of data I do not what two have copies of it.
QUESTION:
Can you suggest a way to transfrom the data using a Cloned version of the original data ?
Cloning won't allow you to actually change data in a clone and not have same change reflected in the original, so if that's what you want you might rethink the cloning idea.
Cloning does give you a separate cursor into the clone and allows you to filter and index (i.e. order) it independently of the master clientdataset. From the data you've provided it looks like you want to filter some branch data and order by branch_id. You can accomplish that by setting up a new filter and index on the clone. Here's a good article that includes examples of how to do that:
http://edn.embarcadero.com/article/29416
Taking a second look at your question, seems like all you'd need to do would be to set up a unique index on branch_id on the cloned dataset. Linked article above has info on how to set up index; check docs on clientdataset.addindex function for more details and info on setting the index to show only unique values, if I recall it may just mean you set branch_id as the primary key.
I can't think of a slick way to do this, but you could index on BRANCH_ID, add an fkInternalCalc boolean field to your dataset, then initialize that field to True on the first row of each branch (using group state or manually) and then filter the clone on the value of the field. You'd have to update the field on data changes though.
I have a feeling that a better solution would be to have a master dataset with a row for each branch.
You don't provide many details about your use case so I'll try to give you some hints:
"A lot of data" suggests that you might have it from a SQL backend. Using a 'SELECT DISTINCT...' or 'SELECT ... GROUP BY BRANCH_ID' (or similar syntax depending on what SQL backend do you) will give the desired result with ease and speed. Please confirm and I'll give you more details.
As the others said a simple 'clone' wouldn't work. The most simpler (and perhaps quicker) sollution, assuming that ussually the brances are few in number WRT to data is to have an index outside of your dataset. If really you want to filter your original data then add a status field (eg boolean) on your data and put a flag (eg. 'True') on the first occurence.
PseudoCode:
(Let's asume that:
your ClientDataSet is cds1
your cds1 have a status field cds1Status (boolean) - this is optional, needed only if you want to sort/filter/search the cds1
you have a lIndex which is a TStringList)
lIndex.Clear;
lIndex.Sorted:=True;
with cds1 do
try
DisableControls;
First;
while not Eof do //scan the dataset
begin
cVal:=cds1Branch_ID.AsString;
Edit; //we anyway update the Status field
if lIndex.Find(cVal, nDummy) then //nDummy - we don't use it.
begin //already in index
cds1Status.AsBoolean:=False; //we say here "No, isn't the 1st occurence"
end
else
begin //Not found! - Well, let's add it...
lIndex.Append(cVal); //update the index
cds1Status.AsBoolean:=True; //mark the first occurence
end;
Post; //save the changes in the status field
Next;
end; //scan
finally
EnableControls; //housekeeping
end;
//WARNING! - NOT tested. I wrote it from my head but I think that you got the idea...
...Depending on what you try to accomplish (which would be the best thing that you might share with us) and what selectivity do you have on BRANCH_ID perhaps the Status engine isn't needed at all. If you have a very low selectivity on that field (selectivity = no. of unique values / no. of records) perhaps it's much faster to have a new dataset and copy there only the unique values rather than putting each record of the original cds in Edit + Post states. (Changing dataset states are costly operations. Especially if your cds is linked to a remote data storage - ie. a server).
hth,
PS: My sollution is intended to be mostly simple. Also you can test with lIndex.Sorted:=False and use lIndex.IndexOf instead of Find. In some (rare) cases is better. Depends on your data. If you want to complicate the things and the speed is really a concern you can implement a full-blown BTree index to do your searces (libraries available). Also you can use the index engine of CDS and index the BRANCH_ID and do many 'Locate' on a clone but because your selectivity is clearly < 1 scaning the cds's entire index theorethically should be slower that a scan on a unique index, especially if your custom-made index is tailored to your data type, structure, distribuition etc.
just my2c